Estimating A Fuzzy Linear Regression For Energy Intensity in Iranian Industrial Sector

In the present study, a case of fuzzy regression model was estimated for iranian industrial energy intensity. to do so, at first the trapezoidal fuzzy values of energy intensity observations were calculated based on the minimizing entropy principle algorithm (mepa) and then a tripled recursive model was estimated for fuzzified energy intensity. because of application of the partial adjustment model, we explored the short-run and long-run membership functions for each of the explanatory variable fuzzy coefficients. the estimation results show that the lagged energy intensity values are the only factor which has a positive effect on the industrial energy intensity attitude, whereas other explanatory variables including energy price, value added share and technical efficiency score have negative effect on energy intensity trend in the period 1982-2006. moreover the estimation results indicated the numerous potential energy saving in iranian industrial sector which is mainly emerged from pure energy intensity in short-run.